GROUP 2 – DIRTBUSTERS
LUCA BESTAGNO
GIOVANNI MANFREDI
MANUEL UCHA RODRIGUEZ
AIKATERINI VASILONIKOLIDAKI
SMITH SODHAN TRIVEDI
EIT DIGITAL SUMMER
SCHOOL 2023:
Methods and Tools for
Resilient Industrial IoT
Business Model Innovation
Touchpo int Sc rubber Dry er Machine
0
INDEX
INDEX
EXECUTIVE SUMMARY ......................................................................................................... 1
TEAM COMPOSITION ............................................................................................................ 2
PROBLEM AND SOLUTION ................................................................................................... 3
CASE DESCRIPTION .......................................................................................................... 3
SOLUTION SUMMARY ....................................................................................................... 3
BUSINESS MODELLING AND PLANNING ........................................................................... 5
VALUE PROPOSITION CANVAS ........................................................................................ 5
SOLUTION ........................................................................................................................... 6
COMPETITOR ANALYSIS ................................................................................................... 7
BUSINESS MODEL CANVAS .............................................................................................. 9
BUSINESS PROCESS MODELLING NOTATION (BPMN) ............................................... 11
BUSINESS DEVELOPMENT PROCESS ............................................................................. 13
PROBLEM IDENTIFICATION ............................................................................................ 13
INTERNAL AND EXTERNAL ANALYSIS ........................................................................... 13
BRAINSTORMING AND IDEATION .................................................................................. 14
INTERVIEWS AND MENTOR INTERACTIONS ................................................................ 14
PROCESS MAPPING ........................................................................................................ 14
PITCH AND FINAL REPORT ............................................................................................. 14
FIGMA DEMO .................................................................................................................... 15
ECONOMIC VIABILITY ..................................................................................................... 18
SELF EVALUTATION AND TEAM REFLECTION ................................................................ 20
LEARNING EXPERIENCE ................................................................................................ 20
SOMETHING TO WORK ON ............................................................................................. 20
REFERENCES ...................................................................................................................... 21
APPENDIX ............................................................................................................................ 22
1
EXECUTIVE SUMMARY
EXECUTIVE SUMMARY
Collaborating closely with Kärcher, a distinguished professional cleaning machine provider,
our recent project aimed to elevate end-user engagement by encouraging the adoption of a
cutting-edge app linked to the innovative cleaning device B 50 W. This endeavour hinged on
creatively harnessing data insights to enrich customer experiences.
The project's significance lays in delving into the challenges faced by service companies
operating in the cleaning sector, aiming to establish novel customer connections. This
insightful experience was made possible through the invaluable guidance of our company
tutor, Bernd Engelhardt, Group Leader for Digital Product Management.
Following the systematic Business Process Engineering approach, our project spanned
multiple meticulous stages, including the utilization of the Value Proposition Canvas, Context
and Competitor Analysis, Comparative Analysis, Business Model Canvas, Business
Ecosystem evaluation, TO BE Process Mapping, and Economic Feasibility assessment.
The Value Proposition Canvas aptly identified and addressed the unique needs of two
customer segments: cleaners and managers. A comprehensive competitor analysis was
conducted to gauge market dynamics and juxtapose our innovation against alternatives.
Leading industry competitors Nilfisk and Tennant were closely examined to validate the
distinctiveness of our solution.
A Comparative Analysis offered a visual validation of our solution's superiority over existing
market offerings, showcasing the data-driven tailored experience, inclusive of on-the-machine
support and training. The Business Model Canvas served to delineate the transition from the
current state (AS-IS) to the new model (TO-BE), accentuating the application's added features.
SIGNAVIO facilitated comprehensive interaction visualization, pivotal in designing a user-
centric application interface to enhance the customer experience.
Our project culminated with an economic viability analysis, encompassing expenditures,
savings, and outcomes evaluated through metrics such as Net Present Value (NPV) and
Payback Time (PBT). Multiple potential scenarios were factored in, underpinning the
comprehensive benefits of our solution.
In conclusion, our project journey encapsulates the synergy of innovation, strategic analysis,
and customer-centric design. Through this collaboration with Kärcher, we not only uncovered
new avenues for customer engagement but also underscored the transformative impact of
data-driven solutions in propelling business growth.
2
TEAM COMPOSITION
TEAM COMPOSITION
A heterogeneous, well-rounded team composed of five members of four different nationalities,
with master’s degrees that include seven different European universities and an American
university.
Legend
DSC: Data Science
PoliMi: Politecnico di Milano, Milan, Italy
UPM: Universidad Politécnica de Madrid, Madrid, Spain
KTH: Kungliga Tekniska Högskolan, Stockholm, Sweden
UF: University of Florida, Gainesville, United States of America
TU/e: Technische Universiteit Eindhoven, Eindhoven, Netherlands
UCA: Université Côte d'Azur, Nice, France
ELTE: Eötvös Loránd Tudományegyetem, Budapest, Hungary
UR1: University of Rennes 1, Rennes, France
!
Luca Bestagno
!
DSC: PoliMi UPM
Manuel Ucha
Rodriguez
"
DSC: UF
Aikaterini
Vasilonikolidaki
#
DSC: TU/e UCA
Smith Sodhan
Trivedi
$
DSC: ELTE UR1
3
PROBLEM AND SOLUTION
PROBLEM AND SOLUTION
CASE DESCRIPTION
Kärcher, a leading provider of cleaning equipment, offers a wide range of professional
products typically targeted at Business Service Cleaners (BSCs). Their approach towards this
customer segment is focused on delivering high-quality products with limited or no interaction
required after purchase, except for regular maintenance.
The project is centred around the “scrubber dryer B 50 W” a product in the professional
category that introduces a new business approach concerning consumer interactions. The
new B 50 W can be operated by using a smartphone app, to configure the machine, monitor
machine parameters during the usage and alert the user in the case of an error. This creates
a permanent channel between Kärcher and the machine operators (typically cleaners) and
between Kärcher and the persons that configure the machine (typically managers).
The main objectives of the project are to assess how this direct channel could impact Kärcher's
business model and whether Kärcher should leverage this change to increase revenue,
enhance customer lifetime value, or streamline processes.
Additionally, the project considers Kärcher's app fragmentation, as the company has
developed various apps for different purposes, leading to confusion and an absence of an
integrated ecosystem.
SOLUTION SUMMARY
The proposed solution is an update to the Machine Connect” application, adding some
functionalities. These are designed for two user groups: the cleaners running the machine and
the managers configuring the machine. Since these users have distinct needs and tasks, their
interaction with the application should be tailored accordingly. To identify the requirements
(pains and gains) of each customer segment, the Value Proposition Canvas was utilised.
This helped to outline the main two goals behind the solution:
increase cleaners’ engagement with their job
simplify the management of the scrubber dryer for the manager.
4
PROBLEM AND SOLUTION
To meet t h e s e g o a l s , thr e e m a i n f e a tures w e r e d e v e l o p ed wit h i n t h e a p p licat i o n :
Gamified training for cleaners: leveraging Kärcher's expertise in operating machines, the
app provides engaging on-the-machine exercises and a structured learning process with
small tasks. This enhances the cleaner-machine relationship and facilitates the learning
process.
Audio entertainment capabilities for cleaners: the application can be connected to external
audio players (using external interfaces), such as Spotify, Apple Music, or other Music (or
Radio, Podcasts) players, to reduce cleaner stress and boredom. Moreover, it enables
companies to provide additional benefits to cleaners, like music or podcast subscriptions.
Data-driven predictive maintenance and machine management for managers: by utilizing
the data already collected from the machine, the app enables predictive maintenance and
tracking of the machine's lifecycle, overall extending it.
These new features contribute to a renovated Kärcher app ecosystem, that we picture as
composed of two distinct applications: one for Home & Garden and one for the Professional
segment. A first step for this integration would be linking the Service” app to “Machine
Connect”, providing an on-the-machine support and more detailed data for effective
maintenance and customer support.
The primary change in Kärcher's Business Model is the establishment of a permanent after-
sales channel. This allows the company to gain insights into how their products are being used
and utilize this knowledge to generate additional revenue through additional services, such as
maintenance, training, and customer support. This approach aligns with industry competitors'
practices (Nilfisk University training, Tennant Gold service support) while surpassing them by
offering a data-driven tailored experience, including on-the-machine support and training.
Addressing data collection concerns, similar practices are already prevalent in various sectors.
Kärcher addresses this by informing users about the purpose and intention behind data
collection, enhancing the overall user experience. Moreover, this data-driven approach aligns
with the company's environmental objectives, as it enables proper employee training and
machine usage, leading to increased efficiency and reduced environmental impact.
A future development of the project would be to leverage the communication channel with
managers to recommend and sell new products. The company could also aim to foster
Kärcher's culture by sharing news and creating communities within the app. As the app's value
to the ecosystem grows, more extensive projects involving the entire ecosystem could be
developed, capitalizing on the data and user interactions collected.
5
BUSINESS MODELLING AND PLANNING
BUSINESS MODELLING AND PLANNING
The business idea aims at understanding if Kärcher's new permanent channel created by the
“Machine Connect” application for the B 50 W scrubber dryer, should be leveraged to increase
revenue, enhance customer lifetime value, or streamline processes.
Two user groups were identified: the cleaners that are operating the machine, and the
managers that are configuring the machine. To identify the requirements (pains and gains) of
each customer segment, the Value Proposition Canvas was utilised.
VALUE PROPOSITION CANVAS
Figure 1 - Value Proposition Canvas - Manager
The gains and pains of the manager that were most considered were: gains (saving resources,
time, and money) and pains (training employees).
Figure 2 - Value Proposition Canvas - Cleaner
6
BUSINESS MODELLING AND PLANNING
The pains of the cleaner that were most considered were: training and repetitive and alienating
work.
The proposed solution takes care of these gains and pains with gain creators: predictive
product maintenance, and pain relievers: in-app training and audio entertainment/education.
In this way it effectively targets both the cleaners operating the machine and the manager
configuring it and keeping track of it.
SOLUTION
The main three features of the application are:
Gamified training for cleaners: leveraging Kärcher's expertise in operating machines, the
app provides engaging on-the-machine exercises and a structured learning process with
small tasks. This enhances the cleaner-machine relationship and facilitates the learning
process.
Audio entertainment capabilities for cleaners: the application can be connected to external
audio players (using external interfaces), such as Spotify, Apple Music, or other Music (or
Radio, Podcasts) players, to reduce cleaner stress and boredom. Moreover, it enables
companies to provide additional benefits to cleaners, like music or podcast subscriptions.
Data-driven predictive maintenance and machine management for managers: by utilizing
the data already collected from the machine, the app enables predictive maintenance and
tracking of the machine's lifecycle, overall extending it.
7
BUSINESS MODELLING AND PLANNING
COMPETITOR ANALYSIS
A competitor analysis has been conducted to investigate the market and confront the
developed idea with alternatives. To do this, the two most prominent Kärcher’s competitors
were considered: Nilfisk and Tennant.
The focus of this analysis is to compare the core products and services offered by competitors,
relevant to our target product. By examining various features and capabilities, the aim is to
gain insights on the competitive strengths of Kärcher and areas for improvement for the
company.
Methodology:
Our analysis was conducted through in-depth research on each company's official website,
product documentation, press releases, and industry reports. The group specifically looked for
features related to smart fleet management, IoT connectivity, predictive maintenance, data
analytics, gamification, direct selling line, interactive training, smart cleaning solutions,
Bluetooth configuration, direct machine support, and remote diagnostics and support.
Nilfisk:
Nilfisk, a prominent player in the cleaning equipment industry, offers a range of services that
include smart fleet management, IoT connectivity, and smart cleaning solutions. While lacking
some advanced features like predictive maintenance, gamification tools, and direct selling
lines offered by its competitor Kärcher, Nilfisk excels in areas such as smart fleet management
and IoT connectivity. Its focus on providing efficient fleet management and seamless
connectivity options makes it a good competitor for customers seeking reliable solutions to
optimize their cleaning operations and enhance overall efficiency.
Tenn a nt:
Tennant, a ke y competitor in th e c l e a n i n g e q u i p m e n t in d u s t r y, off e r s a comprehensiv e set of
services, including IoT connectivity, predictive maintenance, data analytics, smart cleaning
solutions, Bluetooth configuration, direct machine support, and remote diagnostics and
support. Like Kärcher, Tennant provides predictive maintenance and data analytics, making it
a strong contender in the market. However, it lacks gamification tools, a direct selling line, and
interactive training, which are offered by Kärcher. Despite these differences, Tennant's
strengths in IoT connectivity, predictive maintenance, and remote support position it as a
competitive choice for customers seeking advanced cleaning solutions with a focus on data-
driven insights and efficient maintenance practices.
8
BUSINESS MODELLING AND PLANNING
Comparative analysis:
Considering the proposed solution implemented a feature comparison was conducted
between the three companies.
Figure 3 - Competitors comparison
From this analysis, it can be concluded that the solution not only aligns with industry
competitors' practices (such as Nilfisk University training and Tennant Gold service support)
but also surpasses them by offering a data-driven tailored experience, including on-the-
machine support and training.
Overall, the proposed idea demonstrates a well-rounded and forward-looking approach,
making it a superior choice in the market. By addressing diverse customer needs,
incorporating innovative technologies, and providing exceptional support, the proposed app
update has the potential help Kärcher achieve a sustainable competitive advantage keep their
established market lead.
9
BUSINESS MODELLING AND PLANNING
BUSINESS MODEL CANVAS
The change in Kärcher’s business model was tracked throughout the project by first mapping
the AS-IS Business Model, using the Business Model Canvas tool.
Figure 4 - Business Model Canvas - AS-IS
And secondly using the same tool to develop the Business Model TO-BE with the new features
implemented in the app.
Figure 5 - Business Model Canvas - TO-BE
10
BUSINESS MODELLING AND PLANNING
Moving onto the Business Model Canvas, this changes slightly from the current Kärcher’s
Business Model Canvas, creating more revenues associated to services offered in this new
way (training, predictive maintenance, …).
Figure 6 - Business Model Canvas - TO-BE
The changes in the new business model regard an enhancement of the value proposition, that
create a new revenue stream through data-driven recommendations and greater value of the
overall service.
This change also increases the number of activities Kärcher performs, with regard to data
usage and data-driven maintenance.
The new features in the app will also require additional costs and partners, in particular with
regards to machine learning capabilities.
In Figure 6, the business model change is displayed also characterising which kind of impact
will that part have.
11
BUSINESS MODELLING AND PLANNING
BUSINESS PROCESS MODELLING NOTATION (BPMN)
The upcoming section delves into a comprehensive elucidation of the enhancements that will
be incorporated into Business Process Diagrams (BPDs) through the integration of three
pivotal features within the application: Automatic Reordering, Predictive Maintenance, and
Gamification Challenge.
This transformation encompasses a thorough analysis of key stakeholders, primarily the app
users (managers/cleaners), the application interface, the data centre serving as the repository
for all data and algorithmic operations, as well as the entities vital to the process, including B
50 W and Kärcher Warehouses, along with the overarching company structure.
Automatic Reordering
The Automatic Reordering feature operates by leveraging data from consumption product
sensors embedded within the B 50 W unit, as well as the AWS Data Centre. This collaborative
data utilization enables the system to ascertain the machine's average consumption patterns
and determine the optimal quantity for replenishment, thereby ensuring uninterrupted device
functionality.
Figure 7 – BPMN: Automatic Reordering
Predictive Maintenance
12
BUSINESS MODELLING AND PLANNING
Utilizing data collected from sensors, the Predictive Maintenance feature assesses the
machine's condition. It determines if component replacements are needed due to consumption
or critical status, potentially halting operations. The app displays insights with color-coded
notifications. In critical cases, a strategic step is taken, including consultation with a Kärcher
Engineer to prevent machine damage and ensure operational integrity.
Figure 8 - BPMN: Predictive Maintenance
Gamification Challenge
The app includes a Gamification Challenge feature where cleaners can take self-imposed
challenges and earn points based on their performance. This boosts operator motivation and
enhances app usage. The challenging pathways also help users develop their skills.
Additionally, this feature provides valuable data for Kärcher, enhancing their analytical
resources.
Figure 9 - BPMN: Gamification Challenge
13
BUSINESS DEVELOPMENT PROCESS
BUSINESS DEVELOPMENT PROCESS
PROBLEM IDENTIFICATION
Kärcher's introduction of the B 50 W, which can be controlled through a smartphone app
(Machine Connect App), offers several benefits such as machine configuration, parameter
monitoring, error alerts, and user feedback. This opens a permanent communication channel
between Kärcher and machine operators and configurators.
Considering this development, two important questions arise:
How will the direct channel impact Kärcher's business model and interactions with
professional customers? Are significant changes expected in sales, maintenance, and
overall customer engagement?
To c a p i t a l ize o n the d i r e c t c h a n n e l , h o w s h o u l d K ä r c h e r ada p t i t s b u s i n e s s mod e l and
customer journey? Specifically, how can Kärcher increase revenue and enhance
customer satisfaction through this technology integration?
INTERNAL AND EXTERNAL ANALYSIS
A series of analyses were conducted to comprehend the company and its ecosystem better.
These analyses provided diverse insights, aiding the group in identifying potential solutions.
SWOT ANALYSIS
The rise of machine learning and data analysis drives the creation of various applications to
utilize untapped company data. The "Machine Connect" app establishes a direct channel,
addressing the communication gap with end clients and potentially generating additional
revenue streams like maintenance and supplies.
COMPETITORS’ ANALYSIS
Competitors are simplifying training through online courses and apps, benefiting both the
company and managers. Data utilization is prominent among competitors, often via
subscription-based services.
ECOSYSTEM ANALYSIS
The ecosystem analysis highlights the need of the application to consider two main different
users: managers and cleaners.
14
BUSINESS DEVELOPMENT PROCESS
BRAINSTORMING AND IDEATION
With an enhanced grasp of the problem, the company, and its surrounding ecosystem, the
team was well-prepared to initiate ideation. Following an extensive proposal phase, a
classification metric, considering implementation complexity and value proposition, was
employed.
From the generated ideas, the "Gold Mines" (low implementation difficulty, high value yield)
emerged: predictive maintenance, automated re-supply and cleaning staff training via the app.
These concepts underwent refinement using frameworks like the Business Model Canvas and
Value Proposition Canva.
INTERVIEWS AND MENTOR INTERACTIONS
Throughout the project, the group conducted a series of interview with Bernd Engelhardt, the
mentor working in Kärcher. These interview focused on getting the companies view on the
problem and the ecosystem in general, and understand how the current project unfolds.
The interviews have been conducted in a collaborative relationship, leading to a solution
approved by the company that was satisfied with the analysis conducted.
PROCESS MAPPING
In order to deliver a comprehensive mapping of the final application, the Business Process
Modellling Notation (BPMN) was used. This mapping greatly helps mapping out what are the
changes that the application is going to affect.
PITCH AND FINAL REPORT
Significant effort was allocated to skillfully present the project to the jury. The chosen strategy
involved employing the "Nestorian order," encompassing an initial attention-grabbing hook and
a concluding catchphrase designed to leave a lasting impression on the audience. This
approach was selected due to time constraints and the presence of a non-captive audience,
rendering other techniques like ascending or descending climaxes less suitable. Throughout,
the presentation placed a strong emphasis on simplicity.
NEXT SECTIONS
A full Figma demo and Economic analysis were carried out. They are here presented to
complete the Business Development process of the project.
15
BUSINESS DEVELOPMENT PROCESS
FIGMA DEMO
The three innovative features embedded in the Karcher app
are: Smart Training for Cleaners, Audio Entertainment for
Cleaners, and Data-Driven Maintenance for Managers are
developed as a prototype on Figma. These features were
designed to revolutionize the interaction between users and
their cleaning equipment,
enhancing engagement,
efficiency, and overall user
experience. To access the
gamified training, the cleaner
must have a user account.
This is a strategic
requirement which will attract
a higher user engagement.
This paves the way for the
collection of user specific data
that can significantly elevate
the app's value for the cleaning company.
Feature 1: Smart Training for Cleaners
The Smart Training feature is centred around providing users
with an intuitive but also more engaging learning experience,
due to the incorporation of gamification. The games provide training for both technical
knowledge and practical execution
Challenge 1: Understanding Machine
Operations & Settings:
This challenge is mainly designed to teach
cleaners and make them familiar with the
functions associated with each button on
the cleaning machine.
Figure 10 - Prototype
Figure 11 - Training Challenges
Figure 12 - Challenge Machine Operations
16
BUSINESS DEVELOPMENT PROCESS
Challenge 2: Mastering Machine Driving Skills
Skilful navigation through various spaces,
obstacles, and patterns is essential to ensure
thorough cleaning and to optimize time and
resources. Users may struggle with mastering the
driving skills required, leading to potential
inefficiencies and incomplete cleaning.
Challenge 3: Time Trials
Moreover, cleaning efficiency often involves completing tasks within a specific timeframe.
Users might need practice to achieve optimal cleaning speed while maintaining quality.
Quizzes
In addition to hands-on-machine challenges, our prototype introduces
an engaging and informative element through interactive quizzes.
These quizzes are designed as an indicator of the technical
knowledge of the user while reinforcing key concepts related to
machine operations. Users are presented with multiple- choice
options, each corresponding to a specific aspect of the machine's
functionality from which they have to chose the correct answer. Upon
answering the correct answer the cleaner will gain points, while for
wrong answers some points will be deducted.
Leaderboard and Point System
The prototype incorporates a leaderboard and points system to provide
an element of healthy competition and skill enhancement into the
learning process.
As individuals witness their progress and compare it with their peers,
continuous learning and advancement is fostered.
Figure 15 - Machine Driving Skills
Figure 16 Quizzes
Figure 17 - Leader board
17
BUSINESS DEVELOPMENT PROCESS
Feature 2: Audio Education & Entertainment
In the pursuit of revolutionizing the user experience, we
introduce to the Kärcher app a novel feature that transforms
the mundane task of cleaning into an engaging and
informative journey. As demonstrated in Figure 19, the
cleaner will be able to access different forms of audio
entertainment and education, while cleaning such as
listening musing to Spotify or podcasts, following football
matches or Duolingo podcasts. When clicking on an icon, for
example the Spotify icon, the user will be able to access
Spotify via the app and be directed to their favourite music.
Feature 3: Predictive Maintenance for Managers
Using data analytics, the machine data will be used to predict
potential equipment failures or maintenance needs.
The manager can access each machine through the Start Menu
and check for the need of maintenance for each part of the
machine separately.
We use color-coded notifications to provide crucial maintenance
insights. The red alert indicates an urgent need for immediate
attention and inspection of the identified part. On the other hand,
the orange caution serves as a proactive recommendation,
indicating areas that require attention to prevent potential issues
down the line.
Refer to the Appendix for the full prototype link.
Figure 18 - Audio Feature
Figure 19 - Cleaning Mode Audio Feature
Figure 20 - Predictive Maintenance
18
BUSINESS DEVELOPMENT PROCESS
ECONOMIC VIABILITY
This section delves into the economic assessment, encompassing expenditures, savings, and
outcomes measured through Net Present Value (NPV) and Payback Time (PBT). These
metrics are contextualized within diverse potential scenarios to offer a comprehensive view.
Expenditure Analysis
The initial project stage involved detailed cost breakdown, categorized into Capital
Expenditures (CAPEX) for one-time asset expenses and Operating Expenditures (OPEX) for
annual management costs.
CAPEX covers the costs associated with the conceptualization, development and integration
of new app features. This will be possible using a team of dedicated consultants engineers,
whose salaries will be included in OPEX together with AWS data storage and services costs.
Two scenarios were analyzed - optimal app development and contingencies for delays,
considering increased sales thanks to data usage and escalating IT expenses regarding both
engineers and infrastructure.
Values in euros (€)
COST
CAPEX
(WORST)
CAPEX
(BEST)
OPEX
(WORST)
OPEX
(BEST)
search button
6847,826087
4891,304348
predictive maintenance ©
126500
86250
automatic reordering ©
69000
46000
Login
18586,95652
12717,3913
video training
19565,21739
13695,65217
Data Viz ©
80500
57500
API -> background
music/news
44021,73913
31304,34783
Data Base & Services
20500
20500
24600
24600
Company consulting to
analyse data (30% time)
79350
79350
Company consulting to
analyse data (50% time)
132250
132250
Developers (30% time)
67500
67500
Developers (50% time)
112500
112500
Total (year 1)
365021,7391
252358,6957
Total (year 2-3)
167350
167350
Total (year 4-5)
269350
269350
19
BUSINESS DEVELOPMENT PROCESS
Revenue Assessment
Evaluating revenue streams is challenging, especially attributing value to data for product
enhancement and future autonomous driving capabilities. Despite not being in financial
analysis, such intangible values have been acknowledged as they increase the value of the
final solution.
Primary revenue comes from machine sales, starting with 6,000 machines annually. Sales
grow by 2% for standalone machines and 3% with the app. Each machine sells at 25,000
euros with a 10% company margin.
Supplies sales also contribute, priced at 500 euros yearly, growing by 3% without app and 4%
with auto-reordering. An insight from this analysis reveals that 20% of the overall margin can
be attributed to the consumption of these auxiliary products.
Payback Time and Net Present Value
Using previous cost and benefit evaluations, two capital
budgeting methods, NPV and Payback Time (PBT), were
applied to the investment. Economic analysis covered
best and worst-case scenarios, with sensitivity analysis
for the discount rate (k) in both scenarios.
Results show positive NPV even under worst conditions (k = 10). The curves of both cases
are similar, implying delayed app development would still add value to the company.
€ (600.000,00)
€ (400.000,00)
€ (200.000,00)
-
€ 200.000,00
€ 400.000,00
€ 600.000,00
€ 800.000,00
€ 1.000.000,00
1 2 3 4 5
Profit with App
Years
5 Year ROI
Worst
Best
Year
Worst
Best
1
-365022
-252359
2
-376372
-263709
3
-211802
-99138,7
4
66175,46
178838,5
5
645233,9
757896,9
20
SELF EVALUTATION AND TEAM REFLECTION
SELF EVALUTATION AND TEAM REFLECTION
LEARNING EXPERIENCE
Thanks to the project the group was able to understand in a real world scenario, how the
combination of data, with distributed hardware, or Internet of Things (IoT) is able to generate
whole different ways to create value, and so also revenue.
From an application point of view, the project was able to correctly identified the user groups,
that went a long way improving the overall quality of the project. This is something the group
would like to keep in mind in the future, adapting a user-centric design process.
When it regards to group collaborations, many group members gained knowledge and
interesting insights on effective teamwork, delegation, communication, and team-building. A
particular conflict was solved in the group thanks to collective decision making and shared
responsibility among the group members.
Thanks to the collaboration with Kärcher, the whole group gained a deeper knowledge of the
whole cleaning industry, that was lesser known to the majority of the group before the
beginning of the project.
SOMETHING TO WORK ON
The group had different background knowledge on the technical part and on the business side.
The project put a strong emphasis on the business side that was taken care with a lot of tools,
some of which were unknown to some group members.
An insight for the future is to still work as done in this project on the business side when
required, but at the same time integrate it with the personal technical background that many
team members had.
21
REFERENCES
REFERENCES
LINKS
Tennant Website (competitor)
https://www.tennantco.com/en us.html
Nilfisk Website (competitor)
https://investor.nilfisk.com/static-files/7c1bcd3f-e1f6-483c-9ea3-ecfb3e335838
Tennant Solution Data Driven
https://blogs.sap.com/2015/05/22/tennant-re-imagines-its-business-with-iot-
and-big-data/
Audio Streaming Implementation
https://www.audiofetch.com/music-improves-warehouse-productivity/: How
music improves warehouseproductivity
Business Model Canva
https://www.strategyzer.com/canvas/business-model-canvas
Time needed to develop an app
https://spdload.com/blog/how-long-does-it-take-to-develop-an-app/
Signavio Spa (BPMN)
https://www.signavio.com
Karcher Website:
https://www.kaercher.com/it/online-shop.html?cid=it-SEA-
GouCn0wO50mIBcZPQQ9JuQ&gclid=EAIaIQobChMIpu7ssoLsgAMVij8GAB3H1gvqEAAYASAAEgK_W_D_B
wE
Figma:
https://www.figma.com
22
APPENDIX
APPENDIX
Figma Demo - For access to the whole prototype please go to:
https://www.figma.com/proto/o7QXVDDVAi93HJbnYnryWF/Untitled?type=design&node-
id=2- 53&t=BvexjUoDdquApzys-1&scaling=min-zoom&page-id=0%3A1&starting-point-node-
id=2%3A53&show-proto-sidebar=1&mode=design